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Computer-aided diagnosis of atrial fibrillation based on ECG Signals: A review
Arrhythmia is a type of disorder that affects the pattern and rate of the heartbeat. Among the
various arrhythmia conditions, atrial fibrillation (AF) is the most prevalent. AF is associated …
various arrhythmia conditions, atrial fibrillation (AF) is the most prevalent. AF is associated …
AF classification from a short single lead ECG recording: The PhysioNet/computing in cardiology challenge 2017
The PhysioNet/Computing in Cardiology (CinC) Challenge 2017 focused on differentiating
AF from noise, normal or other rhythms in short term (from 9-61 s) ECG recordings …
AF from noise, normal or other rhythms in short term (from 9-61 s) ECG recordings …
A review of atrial fibrillation detection methods as a service
Atrial Fibrillation (AF) is a common heart arrhythmia that often goes undetected, and even if it
is detected, managing the condition may be challenging. In this paper, we review how the …
is detected, managing the condition may be challenging. In this paper, we review how the …
ECG signal classification for the detection of cardiac arrhythmias using a convolutional recurrent neural network
Objective: The electrocardiogram (ECG) provides an effective, non-invasive approach for
clinical diagnosis in patients with cardiac diseases such as atrial fibrillation (AF). AF is the …
clinical diagnosis in patients with cardiac diseases such as atrial fibrillation (AF). AF is the …
Inferior myocardial infarction detection using stationary wavelet transform and machine learning approach
Early and accurate detection of myocardial infarction is imperative for reducing the mortality
rate due to heart attack. Present work proposes a novel technique aiming toward accurate …
rate due to heart attack. Present work proposes a novel technique aiming toward accurate …
Automatic detection of atrial fibrillation based on continuous wavelet transform and 2D convolutional neural networks
Atrial fibrillation (AF) is the most common cardiac arrhythmias causing morbidity and
mortality. AF may appear as episodes of very short (ie, proximal AF) or sustained duration …
mortality. AF may appear as episodes of very short (ie, proximal AF) or sustained duration …
Multiple sclerosis detection based on biorthogonal wavelet transform, RBF kernel principal component analysis, and logistic regression
To detect multiple sclerosis (MS) diseases early, we proposed a novel method on the
hardware of magnetic resonance imaging, and on the software of three successful methods …
hardware of magnetic resonance imaging, and on the software of three successful methods …
Integration of results from convolutional neural network in a support vector machine for the detection of atrial fibrillation
C Ma, S Wei, T Chen, J Zhong, Z Liu… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Atrial fibrillation (AF) can cause a variety of heart diseases and its detection is insufficient in
outside hospital. We proposed three methods for AF diagnosis in ambulatory settings. The …
outside hospital. We proposed three methods for AF diagnosis in ambulatory settings. The …
MINA: multilevel knowledge-guided attention for modeling electrocardiography signals
Electrocardiography (ECG) signals are commonly used to diagnose various cardiac
abnormalities. Recently, deep learning models showed initial success on modeling ECG …
abnormalities. Recently, deep learning models showed initial success on modeling ECG …
A novel interpretable method based on dual-level attentional deep neural network for actual multilabel arrhythmia detection
Arrhythmia accounts for more than 80% of sudden cardiac death, and its incidence rate has
increased rapidly recently. Nowadays, many studies have applied artificial intelligence (AI) …
increased rapidly recently. Nowadays, many studies have applied artificial intelligence (AI) …